Color perception plays an important role in object recognition and scene understanding both for humans and intelligent vision systems. Recent advances in digital color imaging and computer hardware technology have led to an explosion in the use of color images in a variety of applications including medical imaging, content-based image retrieval, biometrics, watermarking, digital inpainting, remote sensing, visual quality inspection, among many others. As a result, automated processing and analysis of color images has become an active area of research, to which the large number of publications of the past two decades bears witness. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for single channel images are often not directly applicable to multichannel ones. The goal of this volume is to summarize the state-of-the-art in the early stages of the color image processing pipeline.However, we limited ourselves to the statistical projection depth case presented in  and defined by h ANOM (x;I) ... Secondly, (Eq. 11) is invariant to affine transformations in the vector space Rd. Third, unfortunately, the exact ... A pseudo-code for a multivariate erosion4 is shown in Algorithm 1 in Matlab notation.
|Title||:||Advances in Low-Level Color Image Processing|
|Author||:||M. Emre Celebi, Bogdan Smolka|
|Publisher||:||Springer Science & Business Media - 2013-12-17|